The Application of Multi-block ADMM on Isotonic Regression Problems
Junxiang Wang, Liang Zhao · arXiv (Cornell University) · 2019
The multi-block ADMM has received much attention from optimization researchers due to its excellent scalability. In this paper, the multi-block ADMM is applied to solve two large-scale problems related to isotonic regression. Numerical experiments show that the multi-block ADMM is convergent when the chosen parameter is small enough and the multi-block ADMM scales well compared with baselines.